14

This reply describes an objective method to measure arbitrary discrepancies between two spatial datasets. Such discrepancies can include shifts of position, changes of shape, and features present in one dataset but not in another. This reply does not provide any means to determine which is "better," because that depends on much more than just the data and ...


10

With the Compare Feature Tool, you should just choose your Segment_ID field as the sort field in the dialog. The [sort] field or fields [are] used to sort records in the Input Base Table and the Input Test Table. The records are sorted in ascending order. Sorting by a common field in both the Input Base Features and the Input Test Features ensures ...


9

In a global dataset you will have cases where a point is close to the equator, or Greenwich meridian. At these points a sign change could leave your location in the same country, but at the wrong location. An alternative approach is to geocode the locations based on the city, county, and country fields. Create a field measuring the distance from the ...


7

This is a good question, naturally isn't obvious how to handle this kind of data. For example, the product State QA has 16 bits and there are single, double and triple bit flags combinations: For example, a bit flag combination as 0-0-0-0-0-0-00-01-001-0-00 means: 00 cloud state: clear 0 cloud shadow: no 001 land/water flag: land 01 aerosol quality: low 00 ...


5

Just a tiny error, as far as I can see. Your substrings are incorrect. This can be seen by comparing the result from a 'which(df$bits="0000100001000100")' with a number of observed unique values, which can be seen in ArcGIS when colouring the tif-file by unique values. 00001000 01000100 = 2116, and there are 3891233 of that number in both ArcGIS and R. This ...


5

Usually terrain models derived from remote sensors will have their initial accuracy evaluated using blind control methods. For example with LIDAR, the remotely sensed measurements are often compared to survey-grade control points (the blind control) taken on the ground in various land covers (woods, open areas, etc) to assess the penetration and accuracy of ...


5

A similar solution to @Matthew's would be to compare your stored lat/long values to that of a freely available City/State/Country dataset. For example, the GeoNames dataset (see under "download server") already contains the Lat/Long values of many city/state/country locations. Doing some simple trigonometry (or if you have the data loaded into a spatial ...


5

Rather relying on online service, you should download a high resolution imagery, geo-reference it accurately and then use as reference for quality assurance. See the resources for fundamentals of georeferencing. Make sure that the RMS error is minimum.


4

Since it is a geometry validation problem from the look of it, load current imagery and see if you can validate the streets as existing or as present. Likely one data set is newer and / or more complete. Find out which dataset has the greatest horizontal accuracy and which has been collected most recently and by what process. Is it a difference between tiger,...


4

Quality control checking in GIS falls under two main categories, geometric and tabular. Since GIS workflows are not standard your QA/QC process is unique to your case. Geometric In general most proprietary and open source GIS applications have a set of tools that check for geometric errors (e.g. ArcGIS Checking and Repairing Geometries, QGIS Check ...


4

See the Overpass API language guide, specifically the section about negation. Not sure what tags Mapbox directions is looking for. Here is an example query for retrieving various roads missing a sidewalk=* key: [out:json][timeout:25]; way["highway"~"primary|secondary|tertiary|residential|unclassified|service"]["sidewalk"!~"."]({{bbox}}); out body; >; ...


4

Satellite data is always shifted. The reason is that accuracy of raster data for large area is not so high (1m, sometimes even 10m) and it will always generate errors. I would suggest to use some location stored for example in point feature which position your are sure about. Also you can use polygon layer with building, if you have one, and measure distance ...


3

Answer from LPDAAC: It goes from 0000 to 1111, with 0000 being the best and 1111 worst. For some reason the table on the product page wasn't complete. To understand what it means and how it could be used you need to understand how it is constructed. Basically we start by assigning a VI_Usefulness of ZERO (0000) and then decrease it based on ...


3

Some literature on this topic: COLOSIMO, G., CRESPI, M., DE VENDICTIS, L., JACOBSEN, K. (2009). Accuracy evaluation of SRTM and ASTER DSMs. In Proceedings of the 29th EARSeL Symposium, Chania, Greece. GOROKHOVICH, Y., & VOUSTIANIOUK, A. (2006). Accuracy assessment of the processed SRTM-based elevation data by CGIAR using field data ...


3

A far as I know, LiDAR signals do not get returned over water bodies. It depends which laser wavelength was used in the survey. If it was a wavelength near the infrared (> 700 nm) it should be partially reflected/absorbed by water, and they are usually considered to be noise (see JeffreyEvan's comment). On the other hand, there are laser wavelengths which ...


2

I recommend this post and this one. Generally, our data should go through to two main Quality Assurance (QA) prisms: 1.Automatic – Checking rules that don’t require the human eye, and, oblige to preordained rules. All those rules you want your data to fit. For example, for the road layer, no dangles. Or buildings shouldn’t intersect roads unless the roads ...


2

I would suggest looking for Esri geodatabase topology rules poster which might be a good start. It shows possible errors and you could use this document as a reference. There is also an extension called ArcGIS Data Reviewer which was designed specifically for QA/QC jobs. It has a lot of functionality, but may be a bit hard to get started. There are a couple ...


2

For vector shifts you can buffer within a radius, anything remaining would need a manual quality assurance. Quality tends to have a manual element unless you are just testing for regression. Address points same operation. Raster look for differences in values tweening pooled versioned data, same with math, any way that is enough for a light overview. Best in ...


2

Have you looked at the ArcGIS Data Reviewer extension? It has lots of great tools that aren't in core ArcGIS. There is also a Data Reviewer for Water Utilities.


2

For each line, you could create the from point using "feature vertices to point". Then you get the spatial join between the man hole and the from points (with INTERSECT), with a join_count field. If you have one intersect, this is OK, zero intersect means that you you don't have line starting from your mahole and 2 intersect mean that both lines end in the ...


2

I have just submitted an ArcGIS Idea for Validation of Hierarchical Fields but since your comment says that your requirement is now for Python I thought I would put together some code showing how to do this using dictionaries. The CityProvinceLookup table has two fields CITY and PROVINCE with a row for each valid combination. The ProvinceCountryLookup ...


2

My answer doesn't provide a proper solution to your issue but just trying to explain the reason of the shift. Any imagery, be it aerial or satellite, intended for mapping has to go through several steps before it is deemed accurate enough for the task. Theses steps involve acquiring ground control points and a DEM for orthorectification and georeferencing ...


2

You are correct: the QA60 bitmask has a value of 1024 for opaque clouds and a value of 2048 for cirrus clouds. The sentinel 2 products are distributed with vector masks that we converted into raster QA bands, reserving the first 9 bits for 3 per-band QA masks for 3 bands. Unfortunately, the source products don't have enough information (yet) for us to ...


2

If you're interested in just using QA information from Bands 1 and 2, this should get you started. Note that most of the code below is the same as yours, just re-organized a bit. You're off to a great start! Also note that the final image collection contains 1159 images, and only the first of those is being added to the map in the final step. var geometry = ...


1

There is an online tool called "OSM Quality Assurance Editor" which queries Overpass API for highways without sidewalk (smoothness, incline, or surface) tags. It was originally developed for improving wheelchair routing. You can log-in with your OSM account using iD or JOSM editor and start improving the map.


1

One option might be to do the same routing using the Street data and then compare the paths, once diverged a given amount flag it so it can be fixed? This would be computationally expensive though as you're going to be comparing lots of distances between two set line segments. You'll need some way of having the path identified to be looked at though unless ...


1

The answer is option 2. As also documented in this post there are undocumented QA-values in the MOD13Q1. I have yet to find a good reason for the lack of documentation, and I expect that you'd have to directly contact the LPDAAC people for a correct answer. Note that in the other post, the observation can be found in the comments-section.


1

Likely just a differing histogram now the mean, max, min, std dev of the raster may be different once the clip is complete. I doubt your pixels values are changing, just the rendering. Overlay a couple of rasters and click on a few pixels to check using the (i) information button.


1

If you're hosting your own feature services from your own ArcGIS for Server, you can publish the feature services off a QAQC version instead of DEFAULT. So, you would have: DEFAULT version --QAQC version When you publish your feature services, you must make sure the data is pointed to the QAQC version. This way when someone adds, removes, or updates ...


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